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ORCIDFeryal M. P. Behbahani
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2020 – today
- 2024
[c12]Edward Hughes, Michael D. Dennis, Jack Parker-Holder, Feryal M. P. Behbahani, Aditi Mavalankar, Yuge Shi, Tom Schaul, Tim Rocktäschel:
Position: Open-Endedness is Essential for Artificial Superhuman Intelligence. ICML 2024- [c11]Jake Bruce, Michael D. Dennis, Ashley Edwards, Jack Parker-Holder, Yuge Shi, Edward Hughes, Matthew Lai, Aditi Mavalankar, Richie Steigerwald, Chris Apps, Yusuf Aytar, Sarah Bechtle, Feryal M. P. Behbahani, Stephanie C. Y. Chan, Nicolas Heess, Lucy Gonzalez, Simon Osindero, Sherjil Ozair, Scott E. Reed, Jingwei Zhang, Konrad Zolna, Jeff Clune, Nando de Freitas, Satinder Singh, Tim Rocktäschel:
Genie: Generative Interactive Environments. ICML 2024 - [i17]Jake Bruce, Michael Dennis, Ashley Edwards, Jack Parker-Holder, Yuge Shi, Edward Hughes, Matthew Lai, Aditi Mavalankar, Richie Steigerwald, Chris Apps, Yusuf Aytar, Sarah Bechtle, Feryal M. P. Behbahani, Stephanie Chan, Nicolas Heess, Lucy Gonzalez, Simon Osindero, Sherjil Ozair, Scott E. Reed, Jingwei Zhang, Konrad Zolna, Jeff Clune, Nando de Freitas, Satinder Singh, Tim Rocktäschel:
Genie: Generative Interactive Environments. CoRR abs/2402.15391 (2024) - [i16]Rishabh Agarwal, Avi Singh, Lei M. Zhang, Bernd Bohnet, Stephanie Chan, Ankesh Anand, Zaheer Abbas, Azade Nova, John D. Co-Reyes, Eric Chu, Feryal M. P. Behbahani, Aleksandra Faust, Hugo Larochelle:
Many-Shot In-Context Learning. CoRR abs/2404.11018 (2024) - [i15]Edward Hughes, Michael Dennis, Jack Parker-Holder, Feryal M. P. Behbahani, Aditi Mavalankar, Yuge Shi, Tom Schaul, Tim Rocktäschel:
Open-Endedness is Essential for Artificial Superhuman Intelligence. CoRR abs/2406.04268 (2024) - [i14]Aviral Kumar, Vincent Zhuang, Rishabh Agarwal, Yi Su, John D. Co-Reyes, Avi Singh, Kate Baumli, Shariq Iqbal, Colton Bishop, Rebecca Roelofs, Lei M. Zhang, Kay McKinney, Disha Shrivastava, Cosmin Paduraru, George Tucker, Doina Precup, Feryal M. P. Behbahani, Aleksandra Faust:
Training Language Models to Self-Correct via Reinforcement Learning. CoRR abs/2409.12917 (2024) - 2023
- [c10]Tom Zahavy, Yannick Schroecker, Feryal M. P. Behbahani, Kate Baumli, Sebastian Flennerhag, Shaobo Hou, Satinder Singh:
Discovering Policies with DOMiNO: Diversity Optimization Maintaining Near Optimality. ICLR 2023 - [c9]Jakob Bauer, Kate Baumli, Feryal M. P. Behbahani, Avishkar Bhoopchand, Nathalie Bradley-Schmieg, Michael Chang, Natalie Clay, Adrian Collister, Vibhavari Dasagi, Lucy Gonzalez, Karol Gregor, Edward Hughes, Sheleem Kashem, Maria Loks-Thompson, Hannah Openshaw, Jack Parker-Holder, Shreya Pathak, Nicolas Perez Nieves, Nemanja Rakicevic, Tim Rocktäschel, Yannick Schroecker, Satinder Singh, Jakub Sygnowski, Karl Tuyls, Sarah York, Alexander Zacherl, Lei M. Zhang:
Human-Timescale Adaptation in an Open-Ended Task Space. ICML 2023: 1887-1935 - [c8]Chris Lu, Yannick Schroecker, Albert Gu, Emilio Parisotto, Jakob N. Foerster, Satinder Singh, Feryal M. P. Behbahani:
Structured State Space Models for In-Context Reinforcement Learning. NeurIPS 2023 - [i13]Adaptive Agent Team, Jakob Bauer, Kate Baumli, Satinder Baveja, Feryal M. P. Behbahani, Avishkar Bhoopchand, Nathalie Bradley-Schmieg, Michael Chang, Natalie Clay, Adrian Collister, Vibhavari Dasagi, Lucy Gonzalez, Karol Gregor, Edward Hughes, Sheleem Kashem, Maria Loks-Thompson, Hannah Openshaw, Jack Parker-Holder, Shreya Pathak, Nicolas Perez Nieves, Nemanja Rakicevic, Tim Rocktäschel, Yannick Schroecker, Jakub Sygnowski, Karl Tuyls, Sarah York, Alexander Zacherl, Lei Zhang:
Human-Timescale Adaptation in an Open-Ended Task Space. CoRR abs/2301.07608 (2023) - [i12]Bernardo Ávila Pires, Feryal M. P. Behbahani, Hubert Soyer, Kyriacos Nikiforou, Thomas Keck, Satinder Singh:
Hierarchical Reinforcement Learning in Complex 3D Environments. CoRR abs/2302.14451 (2023) - [i11]Chris Lu, Yannick Schroecker, Albert Gu, Emilio Parisotto, Jakob N. Foerster, Satinder Singh, Feryal M. P. Behbahani:
Structured State Space Models for In-Context Reinforcement Learning. CoRR abs/2303.03982 (2023) - [i10]Kate Baumli, Satinder Baveja, Feryal M. P. Behbahani, Harris Chan, Gheorghe Comanici, Sebastian Flennerhag, Maxime Gazeau, Kristian Holsheimer, Dan Horgan, Michael Laskin, Clare Lyle, Hussain Masoom, Kay McKinney, Volodymyr Mnih, Alexander Neitz, Fabio Pardo, Jack Parker-Holder, John Quan, Tim Rocktäschel, Himanshu Sahni, Tom Schaul, Yannick Schroecker, Stephen Spencer, Richie Steigerwald, Luyu Wang, Lei Zhang:
Vision-Language Models as a Source of Rewards. CoRR abs/2312.09187 (2023) - 2022
- [j1]Tianhong Dai
, Kai Arulkumaran, Tamara Gerbert, Samyakh Tukra, Feryal M. P. Behbahani, Anil Anthony Bharath:
Analysing deep reinforcement learning agents trained with domain randomisation. Neurocomputing 493: 143-165 (2022) - [c7]Angelos Filos, Eszter Vértes, Zita Marinho, Gregory Farquhar, Diana Borsa, Abram L. Friesen, Feryal M. P. Behbahani, Tom Schaul, André Barreto, Simon Osindero:
Model-Value Inconsistency as a Signal for Epistemic Uncertainty. ICML 2022: 6474-6498 - [i9]Tom Zahavy, Yannick Schroecker, Feryal M. P. Behbahani, Kate Baumli, Sebastian Flennerhag, Shaobo Hou, Satinder Singh:
Discovering Policies with DOMiNO: Diversity Optimization Maintaining Near Optimality. CoRR abs/2205.13521 (2022) - 2021
- [c6]Jessica B. Hamrick, Abram L. Friesen, Feryal M. P. Behbahani, Arthur Guez, Fabio Viola, Sims Witherspoon, Thomas Anthony, Lars Holger Buesing, Petar Velickovic, Theophane Weber:
On the role of planning in model-based deep reinforcement learning. ICLR 2021 - [i8]Angelos Filos, Eszter Vértes, Zita Marinho, Gregory Farquhar, Diana Borsa, Abram L. Friesen, Feryal M. P. Behbahani, Tom Schaul, André Barreto, Simon Osindero:
Model-Value Inconsistency as a Signal for Epistemic Uncertainty. CoRR abs/2112.04153 (2021) - 2020
- [c5]Yutian Chen, Abram L. Friesen, Feryal M. P. Behbahani, Arnaud Doucet, David Budden, Matthew Hoffman, Nando de Freitas:
Modular Meta-Learning with Shrinkage. NeurIPS 2020 - [i7]Pierre-Alexandre Kamienny, Kai Arulkumaran, Feryal M. P. Behbahani, Wendelin Boehmer, Shimon Whiteson:
Privileged Information Dropout in Reinforcement Learning. CoRR abs/2005.09220 (2020) - [i6]Matt Hoffman, Bobak Shahriari, John Aslanides, Gabriel Barth-Maron, Feryal M. P. Behbahani, Tamara Norman, Abbas Abdolmaleki, Albin Cassirer, Fan Yang, Kate Baumli, Sarah Henderson, Alexander Novikov, Sergio Gómez Colmenarejo, Serkan Cabi, Çaglar Gülçehre, Tom Le Paine, Andrew Cowie, Ziyu Wang, Bilal Piot, Nando de Freitas:
Acme: A Research Framework for Distributed Reinforcement Learning. CoRR abs/2006.00979 (2020) - [i5]Thomas Pierrot, Nicolas Perrin, Feryal M. P. Behbahani, Alexandre Laterre, Olivier Sigaud, Karim Beguir, Nando de Freitas:
Learning Compositional Neural Programs for Continuous Control. CoRR abs/2007.13363 (2020) - [i4]Jessica B. Hamrick, Abram L. Friesen, Feryal M. P. Behbahani, Arthur Guez, Fabio Viola, Sims Witherspoon, Thomas Anthony, Lars Buesing, Petar Velickovic, Théophane Weber:
On the role of planning in model-based deep reinforcement learning. CoRR abs/2011.04021 (2020)
2010 – 2019
- 2019
- [c4]Feryal M. P. Behbahani, Kyriacos Shiarlis, Xi Chen, Vitaly Kurin, Sudhanshu Kasewa, Ciprian Stirbu, João Gomes, Supratik Paul, Frans A. Oliehoek, João V. Messias, Shimon Whiteson:
Learning From Demonstration in the Wild. ICRA 2019: 775-781 - [i3]Yutian Chen, Abram L. Friesen, Feryal M. P. Behbahani, David Budden, Matthew W. Hoffman, Arnaud Doucet, Nando de Freitas:
Modular Meta-Learning with Shrinkage. CoRR abs/1909.05557 (2019) - [i2]Tianhong Dai, Kai Arulkumaran, Samyakh Tukra, Feryal M. P. Behbahani, Anil Anthony Bharath:
Analysing Deep Reinforcement Learning Agents Trained with Domain Randomisation. CoRR abs/1912.08324 (2019) - 2018
- [c3]Valliappa Chockalingam, Tegg Tae Kyong Sung, Feryal M. P. Behbahani, Rishab Gargeya, Amlesh Sivanantham, Aleksandra Malysheva:
Extending World Models for Multi-Agent Reinforcement Learning in MALMÖ. AIIDE Workshops 2018 - [i1]Feryal M. P. Behbahani, Kyriacos Shiarlis, Xi Chen, Vitaly Kurin, Sudhanshu Kasewa, Ciprian Stirbu, João Gomes, Supratik Paul, Frans A. Oliehoek, João V. Messias, Shimon Whiteson:
Learning from Demonstration in the Wild. CoRR abs/1811.03516 (2018) - 2016
- [b1]Feryal M. P. Behbahani:
Reverse-engineering the visual and haptic perceptual algorithms in the brain. Imperial College London, UK, 2016 - [c2]Feryal M. P. Behbahani, Guillem Singla-Buxarrais, A. Aldo Faisal:
Haptic SLAM: An Ideal Observer Model for Bayesian Inference of Object Shape and Hand Pose from Contact Dynamics. EuroHaptics (1) 2016: 146-157 - 2015
- [c1]Feryal M. P. Behbahani, Ruth Taunton, Andreas A. C. Thomik, A. Aldo Faisal:
Haptic SLAM for context-aware robotic hand prosthetics - simultaneous inference of hand pose and object shape using particle filters. NER 2015: 719-722
Coauthor Index
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last updated on 2024-10-18 20:33 CEST by the dblp team
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